Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Nearly every day
LLMs used: Google Gemini;ChatGPT;Google Bard;Pi;Microsoft Bing AI 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Digital content creation (e.g., creation of social media content);Analyze data;Generate art;Play games;Get information about current events 
Contexts of LLM use: Work;Personal;Technical 
Prompt 1: What was Elon musk criticized for 
Prompt 2: Best way to get money bg3
Prompt 3: Giants draft analysis 
Prompt 4: Limit for PayPal 1099
Prompt 5: New tax rates 
Prompt 6: Biden newest pardons
Prompt 7: California wild fires 
Prompt 8: Mets free agent signings 
Prompt 9: Baldurs gate 3 tips 
Prompt 10: MLB the show 25 release date
Comments: Nothing else